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name explain-diff-html
description Use when the user asks for a rich explanation of a code change, diff, branch, or PR. Produces HTML output.

Explain Diff

Please make me a rich, interactive explanation of the specified code change.

It should have these sections:

@jscott3201
jscott3201 / custom_pub_chat_template_qwen36.jinja
Created May 25, 2026 17:08
A drop-in replacement chat template for Qwen/Qwen3.6-27B tuned for open-source agentic coding harnesses.
{#---------------------------------------------------------------------
custom_pub_chat_template_qwen36.jinja
=====================================
A public, harness-friendly fork of Qwen's Qwen3.6-27B chat template,
tuned for open-source agentic coding harnesses like:
- anomalyco/opencode (https://github.com/anomalyco/opencode)
- earendil-works/pi (https://github.com/earendil-works/pi)
- openclaw, OpenHarness, similar Claude-Code-style harnesses
WHY THIS FORK EXISTS
@AfterRealm
AfterRealm / BUILD-YOUR-OWN.md
Last active July 6, 2026 05:56
Build Your Own Brain for Claude — a practical guide to persistent memory with Claude Code

Build Your Own Brain for Claude

A practical guide to building a persistent memory system for Claude Code. Based on the Vox Memori architecture — a brain-inspired system that gives Claude genuine continuity across sessions.

What you'll end up with: Claude that remembers you, learns your patterns, tracks your projects, and picks up exactly where you left off — every session.

What you need:

  • Claude Code CLI (Max subscription recommended for off-peak usage)
  • Python 3.10+
  • Basic comfort with SQLite, Python, and JSON

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@fnky
fnky / ANSI.md
Last active July 6, 2026 05:39
ANSI Escape Codes

ANSI Escape Sequences

Standard escape codes are prefixed with Escape:

  • Ctrl-Key: ^[
  • Octal: \033
  • Unicode: \u001b
  • Hexadecimal: \x1B
  • Decimal: 27
@k16shikano
k16shikano / SKILL.md
Last active July 6, 2026 05:37
japanese-tech-writing/SKILL
name japanese-tech-writing
description 日本語の技術文書・書籍原稿の文章規範。整形(一文一行、引用ブロック、脚注、コラム記法)、段落と論証の構成(パラグラフライティング)、論証の厳密さ(ツッコミどころの除去)、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。

日本語技術文書の文章規範

日本語で技術的な原稿(書籍の章、記事、解説文)を書く・推敲するときは、以下の規範に従う。

整形